Sectoral Wage Convergence: A Nonparametric Distributional Analysis
The large shift of U.S. employment from goods producers to service producers has generated concern over future income distribution because of perceived large relative pay differences. This paper applies a density overlap statistic to compare the sectors’ distribution of weekly wages at all wage levels. A simple refinement yields locational information by decile. To counter problematic features of Current Population Survey data--namely, sampling variation at infrequent wage rates and extensive rounding at common wage rates--we employ nonparametric density-estimation procedures to isolate the underlying shapes of the densities. The validity and accuracy of the estimation procedures are evaluated with simulations designed to fit the dataset. Bootstrapped standard errors and confidence intervals are calculated to indicate the statistical significance of the results.
Schweitzer, Mark E., and Max Dupuy. 1995. “Sectoral Wage Convergence: A Nonparametric Distributional Analysis” Federal Reserve Bank of Cleveland, Working Paper No. 95-20. https://doi.org/10.26509/frbc-wp-199520